Dr. Manuel Nietert

Group Leader Chemoinformatics and Imaging at the UMG

Telephone: 0551/39-61789

E-Mail: manuel.nietert@med.uni-goettingen.de

Location: Goldschmidtstr. 1, 2. OG, Room: 2.112

ORCID ID: https://orcid.org/0000-0001-5443-7943

Work Affiliations:

Group of Chemoinformatics and Imaging - UMG

Curriculum Vitae

Since 2023   Project Coordinator, ERAPerMed Stracyfic, UMG, Germany
2022 - 2024 Interim Professorship for Informatics at the University of Applied Science and Arts - Faculty of Engineering and Health HAWK, Germany
Since 2019   Project Leader, AutoBuSTeD, UMG, Germany
Since 2018 Group Leader of Applied Bio(chem)informatics and Image Analysis in the Department of Medical Bioinformatics, UMG, Germany
2017 - 2024  Project Leader, CandActCFTR, UMG, Germany 
2013 - 2016  Researcher & Project manager, MetastaSys, UMG, Germany
2010 - 2013  Researcher & Project manager, BreastSys, UMG, Germany 
2007 - 2009  Research Assist., Dept. of Microbiology and Genetics, TU Darmstadt, Germany
08/2008  PhD in Chemistry, Goethe University, Frankfurt a. M. - Germany
08/2004  Master Level Degree in Biochemistry, Goethe University, Frankfurt a. M., Germany

Awards/ Academic Roles

2022/10 to 09/2024 Interim Professorship for Informatics at the University of Applied Science and Arts - Faculty of Engineering and Health HAWK

In July 2022 we received the LIFT-OFF 2022 Gründungswettbewerb award of the Georg-August-University Göttingen - 2. place in the category science.

In October 2022 we received together with our partners from the Hannover Medical School (MHH)  the decission notification that our next clinical study "The β-adrenergic sweat secretion test using AutoBuSTeD software as a novel diagnostic tool in patients with CFTR dysfunction" will be funded by the German Patient Organisations Mukoviszidose Institut gemeinnützige Gesellschaft für Forschung und Therapieentwicklung mbH small project funding program.

Also in October 2022 we reveived the decission notification that we will receive funding from the ERAPerMed joint transnational call 2022 program for further developing the standardization of the test for our project submission "Patient Stratification by Standardization of the Image-based Sweat Test for Cystic Fibrosis for use in Clinical Routine" . Where I will be working with our partners from Belgium, France, Germany and Italy together with the partners of the European patient organisation to bring the test to a clinical routine use level. The project started in 2023 and more information can be found here.

Christiane Herzog-Foundations “Forschungsförderpreis für wissenschaftliche Nachwuchsförderung 2018”, initial funding for the Automatic bubble sweat test diagnostic project – AutoBuSTeD

Former Vice spokesperson of the working group Data quality and transparency in medical research of the TMF e.V. - the umbrella organization for networked medical research in Germany.

Member of the FAIRDOM Systems Biology Developers Foundry since 2012

Research focus

Major Research Interests

For the past years we focus our research in the field of cystic fibrosis (CF), where we still see an unmet demand for IT solutions to help this field. In general our work group aims at providing IT based solutions for biochemical aspects of the systems biology and systems medicine projects, but if necessary can even venture out to help improve the acquisition setup. We thus develop and adapt software solutions to provide the required tools for medical research.

At a first glance, CF is a monocausal disease in which over 2000 putative mutations leading to various forms of phenotypes have been identified. Among these, about 300 variants define the more common types.
The CFTR protein is only effective as an integral membrane protein, and as such, it is affected by transcription, translation, folding and degradation, as well as protein traficking processes. Thus, this monogenic disease has multiple sites for potential drug intervention during its life cycle and covers also protein structure variants. This makes it an interesting target for a system medicine approach. The life cycle of the protein offers also multiple modes to obtain information to annotate the system and the existing literature offers various annotations for specific combinations of mutations and read-outs (e.g. protein expression, functional patch clamp measurements, up to structure models and molecular dynamic simulations).

Current Projects

Automated Bubble Sweat Test Diagnostics – AutoBuSTeD -

s.gwdg.de/xv5Uzr

AutoBuSTeD is an example of the work we do on the automation of image analysis workflows, e.g. the AutoBuSTeD project, and we also cover various other image input sources for other projects as well. E.g. microscopy data in the project Pulmonary transplantation of macrophages as a cellbased therapy to treat chronic infections in the cystic fibrosis lung, where we are the collaboration partner to automate the LysoSensor image analysis.

Curated database of candidate therapeutics for the activation of CFTR-mediated ion conductance – CandActCFTR –

s.gwdg.de/xvtIlC

CandActCFTR is a curated compound database which annotates the chemical structure library with information on where and how in the protein life cycle a compound likely interacts, thus comprising a good starting point for modelling the disease and enhancing ligand based approaches. In the upcoming extension of CandActCFTR, this ligand-based approach will be complemented by structure-based annotations, including the means to predict the interactions between CandActCFTR substances and CFTR by using existing molecular dynamics trajectories, and by adding more organisation and annotation modules

Publications

  1. Rodriguez Gonzalez, C.; Basílio-Queirós, D.; Neehus, A.-L.; Merkert, S.; Tschritter, D.; Ünal, S.; Hegermann, J.; Mörgelin, M.; Bustamante, J.; Nietert, M. M.; Martin, U.; Tümmler, B.; Munder, A.; Lachmann, N. Human CFTR Deficient iPSC-Macrophages Reveal Impaired Functional and Transcriptomic Response upon Pseudomonas Aeruginosa Infection. Front. Immunol. 2024, 15. https://doi.org/10.3389/fimmu.2024.1397886.

  2. Wei, W.; Lattau, S. S. J.; Xin, W.; Pan, Y.; Tatenhorst, L.; Zhang, L.; Graf, I.; Kuang, Y.; Zheng, X.; Hao, Z.; Popa-Wagner, A.; Gerner, S. T.; Huber, S.; Nietert, M.; Klose, C.; Kilic, E.; Hermann, D. M.; Bähr, M.; Huttner, H. B.; Liu, H.; Fitzner, D.; Doeppner, T. R. Dynamic Brain Lipid Profiles Modulate Microglial Lipid Droplet Accumulation and Inflammation Under Ischemic Conditions in Mice. Advanced Science 2024, n/a (n/a), 2306863. https://doi.org/10.1002/advs.202306863.

  3. Bachanek, S.; Wuerzberg, P.; Biggemann, L.; Janssen, T. Y.; Nietert, M.; Lotz, J.; Zeuschner, P.; Maßmann, A.; Uhlig, A.; Uhlig, J. Renal Tumor Segmentation, Visualization, and Segmentation Confidence Using Ensembles of Neural Networks in Patients Undergoing Surgical Resection. Eur Radiol 2024. https://doi.org/10.1007/s00330-024-11026-6.

  4. Lattau, S. S. J.; Borsch, L.-M.; Auf Dem Brinke, K.; Klose, C.; Vinhoven, L.; Nietert, M.; Fitzner, D. Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS). IJMS 2024, 25 (5), 2483. https://doi.org/10.3390/ijms25052483.

  5. Pallenberg S. T., Held I., Dopfer C., Minso R., Nietert M.M., Hansen G., Tümmler B., and Dittrich A.M..
    Differential Effects of ELX/TEZ/IVA on Organ-Specific CFTR Function in Two Patients with the Rare CFTR Splice Mutations c.273+1G>A and c.165-2A>G. 
    Frontiers in Pharmacology, Sec. Pharmacology of Ion Channels and Channelopathies, 14 (March 15, 2023). https://doi.org/10.3389/fphar.2023.1153656.

  6. Vinhoven L.; Stanke F.; Hafkemeyer S.; Nietert M.:
    Complementary Dual Approach for In Silico Target Identification of Potential Pharmaceutical Compounds in Cystic Fibrosis. 
    International Journal of Molecular Sciences, Section Biochemistry, Special Issue: Small Molecule Drug Design and Research (accepted October 2022). https://www.mdpi.com/1422-0067/23/20/12351

  7. Voskamp  M.; Vinhoven L.; Stanke F.; Hafkemeyer S.; Nietert M.:
    Integrating Text Mining into the Curation of Disease Maps.
    Biomolecules 12, no. 9 (September 2022): 1278. https://doi.org/10.3390/biom12091278.

  8. Nietert M.Vinhoven L.; Auer F.; Hafkemeyer S.; Stanke F.:
    Comprehensive analysis of chemical structures that have been tested as CFTR activating substances in a publicly available database CandActCFTR
    Frontiers in Pharmacology,2021. https://www.frontiersin.org/articles/10.3389/fphar.2021.689205

  9. Pallenberg S., T.; Junge S.; Ringshausen C.; F., Sauer-Heilborn A.; Hansen G.; Dittrich A., M.; Tümmler B.; Nietert M.:
    CFTR modulation with elexacaftor-tezacaftor-ivacaftor in people with cystic fibrosis assessed by the β-adrenergic sweat rate assay
    Journal of Cystic Fibrosis,2021. https://doi.org/10.1016/j.jcf.2021.10.005

  10. Vinhoven L.; Voskamp M.; Nietert M.M.
    Mapping Compound Databases to Disease Maps—A MINERVA Plugin for CandActBase. 
    J. Pers. Med. 2021, 11, 1072. doi.org/10.3390/jpm11111072

  11. Vinhoven L.; Stanke F.; Hafkemeyer S.; Nietert M.M.
    CFTR Lifecycle Map—A Systems Medicine Model of CFTR Maturation to Predict Possible Active Compound Combinations.
    Int. J. Mol. Sci. 2021, 22(14), 7590; https://doi.org/10.3390/ijms22147590; accepted Jul 2021.

  12. Bleckmann A, Kirchner B, Nietert M, Peeck M, Balkenhol M, Egert D, Rohde TV, Beißbarth T, Pukrop T.
    Impact of pre-OP independence in patients with limited brain metastases on long-term survival.
    BMC Cancer. 2020 Oct 8;20(1):973. PMID: 33032552 doi.org/10.1186/s12885-020-07459-z.

  13. Jo P, Bernhardt M, Nietert M, König A, Azizian A, Schirmer MA, Grade M, Kitz J, Reuter-Jessen K, Ghadimi M, Ströbel P, Schildhaus HU, Gaedcke J.
    KRAS mutation status concordance between the primary tumor and the corresponding metastasis in patients with rectal cancer.
    PLoS One. 2020 Oct 1;15(10):e0239806. eCollection 2020. PMID: 33002027 doi.org/10.1371/journal.pone.0239806.

  14. Uhlig J, Biggemann L, Nietert MM, Beißbarth T, Lotz J, Kim HS, Trojan L, Uhlig A.
    Discriminating malignant and benign clinical T1 renal masses on computed tomography: A pragmatic radiomics and machine learning approach.
    Medicine (Baltimore). 2020 Apr;99(16):e19725. PMID: 32311963 doi.org/10.1097/MD.0000000000019725.

  15. Jo P, Kesruek H, Nietert M, Sahlmann C, Gaedcke J, Ghadimi M, Sperling J.
    Inzidenz und Prädiktive Faktoren des Bilateralen Papillären Schilddrüsenkarzinoms.
    Zentralblatt für Chirurgie. 2018 Aug;143(4):361-366. Epub 2018 Aug 22, PMID: 30134494 doi.org/10.1055/a-0651-0878.

  16. Lowes M, Kleiss M, Lueck R, Detken S, Koenig A, Nietert M, Beissbarth T, Stanek K, Langer C, Ghadimi M, Conradi LC, Homayounfar K.
    The utilization of multidisciplinary tumor boards (MDT) in clinical routine: results of a health care research study focusing on patients with metastasized colorectal cancer.
    International journal of colorectal disease. 2017; PMID: 28779354, PMCID: PMC5596058, dx.doi.org/10.1007%2Fs00384-017-2871-z

  17. Linke F, Harenberg M, Nietert M, Zaunig S, von Bonin F, Arlt A, Szczepanowski M, Weich HA, Lutz S, Dullin C, Janovská P, Krafčíková M, Trantírek L, Ovesná P, Klapper W, Beissbarth T, Alves F, Bryja V, Trümper L, Wilting J, Kube D.
    Microenvironmental interactions between endothelial and lymphoma cells: a role for the canonical WNT pathway in Hodgkin lymphoma.
    Leukemia. 2017; 31(2):361-372. PMID: 27535218 doi.org/10.1038/leu.2016.232

  18. Linke F, Zaunig S, Nietert M, von Bonin F, Lutz S, Dullin C, Janovská P, Beissbarth T, Alves F, Klapper W, Bryja V, Pukrop T, Trümper L, Wilting J, Kube D.
    WNT5A: a motility-promoting factor in Hodgkin lymphoma.
    Oncogene. 2017; 36(1):13-23. PMID: 27270428 doi.org/10.1038/onc.2016.183

  19. Rühlmann F, Nietert M, Sprenger T, Wolff HA, Homayounfar K, Middel P, Bohnenberger H, Beissbarth T, Ghadimi BM, Liersch T, Conradi LC.
    The Prognostic Value of Tyrosine Kinase SRC Expression in Locally Advanced Rectal Cancer.
    Journal of Cancer. 2017; 8(7):1229-1237. PMID: 28607598, PMCID: PMC5463438 dx.doi.org/10.7150/jca.16980

  20. Jo P, Nietert M, Gusky L, Kitz J, Conradi LC, Müller-Dornieden A, Schüler P, Wolff HA, Rüschoff J, Ströbel P, Grade M, Liersch T, Beißbarth T, Ghadimi MB, Sax U, Gaedcke J.
    Neoadjuvant Therapy in Rectal Cancer - Biobanking of Preoperative Tumor Biopsies.
    Scientifc reports. 2016; 6:35589. PMID: 27752113, PMCID: PMC5067705 doi.org/10.1038/srep35589

  21. Styczen H, Nagelmeier I, Beissbarth T, Nietert M, Homayounfar K, Sprenger T, Boczek U, Stanek K, Kitz J, Wolff HA, Ghadimi BM, Middel P, Liersch T, RüschoffJ, Conradi LC.
    HER-2 and HER-3 expression in liver metastases of patients with colorectal cancer.
    Oncotarget. 2015; 6(17):15065-76. PMID: 25915155, PMCID: PMC4558136 dx.doi.org/10.18632%2Foncotarget.3527

  22. von der Heyde S, Wagner S, Czerny A, Nietert M, Ludewig F, Salinas-Riester G, Arlt D, Beißbarth T.
    mRNA profling reveals determinants of trastuzumab efciency in HER2-positive breast cancer.
    Public Library of Science One. 2015; 10(2):e0117818. PMID: 25710561, PMCID: PMC4339844 dx.doi.org/10.1371%2Fjournal.pone.0117818

  23. Conradi LC, Styczen H, Sprenger T, Wolff HA, Rödel C, Nietert M, Homayounfar K, Gaedcke J, Kitz J, Talaulicar R, Becker H, Ghadimi M, Middel P, Beissbarth T, Rüschoff J, Liersch T.
    Frequency of HER-2 positivity in rectal cancer and Prognosis.
    The American journal of surgical pathology. 2013; 37(4):522-31. PMID: 23282976 doi.org/10.1097/pas.0b013e318272ff4d

  24. Tanrikulu Y, Nietert M, Scheffer U, Proschak E, Grabowski K, Schneider P, Weidlich M, Karas M, Göbel M, Schneider G.
    Scafold hopping by fuzzy pharmacophores and its application to RNA targets.
    Chembiochem : a European journal of chemical biology. 2007; 8(16):1932-6. PMID: 17896338 doi.org/10.1002/cbic.200700195

  25. Böcker A, Sasse BC, Nietert M, Stark H, Schneider G.
    GPCR targeted library design: novel dopamine D3 receptor ligands.
    ChemMedChem: Chemistry Enabling Drug Discovery. 2007; 2(7):1000-5. PMID: 17477344 doi.org/10.1002/cmdc.200700067

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